基于天线选择和功率分配的联合迭代优化算法

当使用所有天线进行无线数据传输时，大规模多输入多输出（Multiple-Input multiple-Output,MIMO）系统中的基站需要使用与天线数相同的射频链路，导致系统的实现复杂度增加，降低了系统的能效。针对能效降低的问题，提出了一种天线选择和功率分配的联合迭代优化算法。该算法在给定初始发送功率的条件下，随机生成一个天线集合作为内循环的初始值，内循环每次从余下的天线集合中选择一根具有最大能效的天线进行替换，得出最优天线集合，求出相应的最优发送功率，并以此作为下次外循环发送功率的初始值。仿真结果表明，所提算法在降低计算复杂度的前提下，几乎可以达到近似于最优穷举搜索算法的能效性能。

A Jointly Iterative Optimization Algorithm Based on Antenna Selection and Power Allocation

Using the same number of radio frequency chains as the antennas at the base station for wireless data transmission in massive multiple-input multiple-output(MIMO) systems will increase the system complexity and reduce the energy efficiency.To solve this problem,a jointly iterative optimization algorithm based on antenna selection and power allocation is proposed.It randomly generates an active transmit antenna subset under the certain initial transmit power as the initialization of the inner loop.In the inner loop,the optimal active antenna subset is obtained by updating each entry of antenna subset with the best one selected from the inactive antenna subset,which results in the maximum energy efficiency.Moreover,the corresponding optimal transmit power is achieved as the initial transmit power of the next outer loop.Simulation results show that the proposed algorithm can not only reduce the computational complexity,but also achieve almost the same energy efficiency as the exhaustive search algorithm.